Enhancing Fuel Economy and Emission Performance of Dual-Motor PHEVs via a Robust Adaptive ECMS Control Framework

The energy efficiency of plug-in hybrid electric vehicles (PHEVs) is critically influenced by their energy management strategies, particularly in dual-motor architectures. This study proposes a novel dual static Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) controller to enhance fuel economy, emission performance, and the robustness of this controller designed to optimize fuel economy and emission performance while maintaining robustness against external disturbances in dual-motor PHEVs. The proposed method dynamically adjusts equivalent consumption factors based on driving conditions, addressing limitations of traditional fixed-factor ECMS approaches. Comparative experiments were conducted under standard and disturbed driving cycles, using rule-based (RB) control and conventional ECMS as benchmarks. The results demonstrate that A-ECMS improves fuel economy by 7.8% and reduces CO₂ emissions by 15.14 g/km under nominal conditions. Even with 5% random noise introduced to test robustness, A-ECMS maintains a 6.9% fuel economy improvement and achieves a 14.39% CO₂ reduction relative to ECMS. Furthermore, in two representative scenarios, the A-ECMS strategy yields cost savings of 30.17% and 28.56%, respectively. These findings confirm the robustness, adaptability, and economic advantage of A-ECMS, offering valuable insights for the real-time control of hybrid powertrains in future low-carbon mobility solutions.